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Fleak AI Workflows

Low-code API builder for data teams to simplify AI workflows.

10k 热度 AI开发平台 Serverless API AI workflows Data integration Real-time monitoring Low-code platform Dynamic API builder Version control Cloud integration
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软件新闻

VMware nods to AI but looks to long-term

发布日期:2025-09-11

Owner of VMware, Broadcom, announced that its VMware Cloud Foundation platform is now AI native at the VMware Explore conference a few weeks ago. It was the latest move by the company to keep up to speed with the rest of the technology industry’s wide and rapid adoption of large language models, yet came as […] The post VMware nods to AI but looks to long-term appeared first on AI News.

Yext Scout Guides Brands Through AI Search Challenges

发布日期:2025-09-11

Customers are discovering brands and learning about products and services in new ways from traditional search to AI search, to AI agents and more, the discovery journey has completely changed, and brands need to adapt to the new paradigm. Launched earlier this year, Yext Scout is an AI search and competitive intelligence agent that’s designed […] The post Yext Scout Guides Brands Through AI Search Challenges appeared first on AI News.

SoundHound Vision AI:当语音助手获得视觉能力,多模态交互迎来新突破

发布日期:2025-08-12

语音AI领域的领军企业SoundHound近日发布革命性Vision AI系统,将视觉识别与语音技术深度融合。这项技术突破让AI能够同时处理视觉和听觉信息,实现真正意义上的多模态交互。从汽车导航到工业维修,从零售盘点到餐饮点单,Vision AI正在重新定义人机交互的边界,为各行业带来更自然、更智能的解决方案。

使用指南

What is Fleak?

Fleak is a low-code serverless API builder designed to simplify AI workflows for data teams without requiring infrastructure.

How to use Fleak?

Configure essential components of your data workflow, transform data, and integrate LLMs with ease on Fleak.

Fleak's Core Features

Serverless architecture for scalable AI workflows

Dynamic API builder for complex model chaining

Real-time monitoring of performance and correctness

Integration with cloud data warehouses and vector databases

Fleak's Use Cases

#1

Summarizing text and generating embeddings for storage in Pinecone

#2

Automating personalized email workflows using SQL and LLMs

#3

Enhancing LLM responses with Retrieval-Augmented Generation (RAG)

FAQ from Fleak

What is Fleak?

Can Fleak handle real-time data processing?

Is Fleak suitable for production environments?

What types of workflows can I build with Fleak?

Fleak Support Email & Customer service contact & Refund contact etc.

Here is the Fleak support email for customer service:

[email protected]

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More Contact, visit

the contact us page(https://fleak.ai/contact)

Fleak Company

Fleak Company name:

Fleak.ai

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More about Fleak, Please visit

the about us page(https://fleak.ai/company)

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Fleak Pricing

Fleak Pricing Link:

https://fleak.ai/pricing

Fleak Youtube

Fleak Youtube Link:

https://x.com/getonfleak

Fleak Linkedin

Fleak Linkedin Link:

https://www.linkedin.com/company/fleak/

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